Current Research (please see publications for details)

• Next-Generation Waveform Design (下世代通訊系統波形設計)

Developed an improved transmission waveform compatible with 4G LTE/5G NR standards and reduced the peak-to-average power ratio (PAPR) to enhance power efficiency and save energy in end-user devices.

在相容於現行4G LTE/5G NR之波形前提下，設計低峰均功率比(PAPR)之傳輸波形，提升終端裝置功率發射效率，增強省電效果。

• Index Modulation (索引調變)

Applying the index modulation technique, originally used for multi-antenna systems, to the subcarriers in OFDM systems significantly enhances the trade-off flexibility between spectral efficiency (SE) and energy efficiency (EE) in communication systems.

將原用於多天線系統的索引調變技術運用於正交分頻多工(OFDM)系統中的子載波，大幅增加通訊系統頻譜效益(SE)與能量效益(EE)之權衡彈性。

• Nonlinear Noise Compensation (非線性雜訊補償)

Utilizing the generalized Papoulis-Gerchberg algorithm and leveraging known system information to compensate for the nonlinear distortion caused by power amplifiers (PA) and impulse noise in wireless communication systems, thereby reducing the bit error rate (BER) of the transmitted signals from IoT devices.

以廣義帕波式迭代演算法(generalized Papoulis-Gerchberg algorithm)利用已知系統資訊來補償無線通訊系統中功率放大器(PA)與脈衝雜訊(impulse noise)所造成之非線性失真，降低物聯網裝置所發送之位元錯誤率(BER)。

• O-RAN RIC xApp for 5G gNB KPI Improvement (O-RAN RIC 5G應用開發)

Open Radio Access Network (O-RAN) is a rapidly evolving network deployment technology in recent years. By developing the RAN Intelligent Controller (RIC), AI can directly control the parameters of 5G base stations (gNB), enabling automatic optimization of complex 5G networks and enhancing network performance.

開放性無線接入網路 (Open radio access network，O-RAN)為近年急速發展之新式網路佈署技術，透過對RIC (RAN Intelligent Controller)的開發使AI可直接控制5G基站(gNB)參數，自動優化複雜的5G網路，提升網路效能。

• Microgrid of Regenerable Powered Base Station (再生能源基地台微電網)

To mitigate the increased power consumption in base stations driven by the high-speed demands of next-generation communication systems, we optimize the solar photovoltaic and battery storage systems in renewable energy base stations through machine learning techniques.

為因應下世代通訊系統高速需求所造成之基站總耗電量大幅上升，以機器學習方法優化再生能源基站之太陽能光伏系統及電池儲能系統。